Kernel herding
Project description
herding
Kernel herding is a kind of quasi-monte carlo where samples are chosen successively to approximate known kernel moment constraints.
In the video also linked below, the green dots are landmark locations y and the expected value of a gaussian kernel E[ker(x,y)] is assumed known for the desired distribution for x, which happens to be Gaussian.
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